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Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned…

Applications · Statistics 2014-08-08 William Fithian , Jane Elith , Trevor Hastie , David A. Keith

Marine mammals are increasingly vulnerable to human disturbance and climate change. Their diving behavior leads to limited visual access during data collection, making studying the abundance and distribution of marine mammals challenging.…

Presence/absence data and presence-only data are the two customary sources for learning about species distributions over a region. We illuminate the fundamental modeling differences between the two types of data. Most simply, locations are…

Methodology · Statistics 2019-04-04 Alan. E. Gelfand , Shinichiro Shirota

Accurately identifying spatial patterns of species distribution is crucial for scientific insight and societal benefit, aiding our understanding of species fluctuations. The increasing quantity and quality of ecological datasets present…

In ecology we may find scenarios where the same phenomenon (species occurrence, species abundance, etc.) is observed using two different types of samplers. For instance, species data can be collected from scientific sampling with a…

Presence-only data, point locations where a species has been recorded as being present, are often used in modeling the distribution of a species as a function of a set of explanatory variables---whether to map species occurrence, to…

Applications · Statistics 2010-11-16 David I. Warton , Leah C. Shepherd

1. Species distribution models (SDM) are tools used to determine environmental features that influence the geographic distribution of species' abundance and have been used to analyze presence-only records. Analysis of presence-only records…

Populations and Evolution · Quantitative Biology 2013-12-05 Trevor Hefley , Andrew Tyre , David Baasch , Erin Blankenship

In ecology, photogrammetry is a crucial method for efficiently collecting non-destructive samples of natural environments. When estimating the spatial distribution of animals, detecting objects in large-scale images becomes crucial. Object…

In fisheries ecology, species abundance data are often collected by multiple surveys, each with unique characteristics. This article is motivated by a dataset of Atlantic sea scallop abundance records along the northeast coast of the United…

Applications · Statistics 2026-04-03 Quan Vu , Francis K. C. Hui , A. H. Welsh , Samuel Muller , Eva Cantoni , Christopher R. Haak

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence…

Quantitative Methods · Quantitative Biology 2024-06-18 Robin Zbinden , Nina van Tiel , Benjamin Kellenberger , Lloyd Hughes , Devis Tuia

The social structure of an animal population can often influence movement and inform researchers on a species' behavioral tendencies. Animal social networks can be studied through movement data; however, modern sources of data can have…

In this paper we present a discrete dynamical population modeling of invasive species, with reference to the swamp crayfish Procambarus clarkii. Since this species can cause environmental damage of various kinds, it is necessary to evaluate…

Populations and Evolution · Quantitative Biology 2012-10-16 Gianluca Martelloni , Franco Bagnoli , Stefano Marsili Libelli

Species distribution models (SDMs) are increasingly used in ecology, biogeography, and wildlife management to learn about the species-habitat relationships and abundance across space and time. Distance sampling (DS) and capture-recapture…

Methodology · Statistics 2022-03-09 Narmadha M. Mohankumar , Trevor J. Hefley , Katy Silber , W. Alice Boyle

Models for accurately predicting species distributions have become essential tools for many ecological and conservation problems. For many species, presence-background (presence-only) data is the most commonly available type of spatial…

Methodology · Statistics 2018-01-08 Yan Wang , Lewi Stone

Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work we present a Bayesian approach to the…

Computation · Statistics 2013-05-07 Fabio Divino , Natalia Golini , Giovanna Jona Lasinio , Antti Penttinen

Social interactions are fundamental in animal groups, including humans, and can take various forms, such as competition, cooperation, or kinship. Understanding these interactions in marine environments has been historically challenging due…

Quantitative Methods · Quantitative Biology 2025-10-22 Juan Fernández-Gracia , Jorge P. Rodríguez , Lauren R. Peel , Konstantin Klemm , Mark G. Meekan , Víctor M. Eguíluz

Sustainable management of marine ecosystems is vital for maintaining healthy fishery resources, and benefits from advanced scientific tools to accurately assess species distribution patterns. In fisheries science, two primary data sources…

Presence-absence data is defined by vectors or matrices of zeroes and ones, where the ones usually indicate a "presence" in a certain place. Presence-absence data occur for example when investigating geographical species distributions,…

Methodology · Statistics 2021-11-24 Gabriele d'Angella , Christian Hennig

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting environmental conditions to species occurrences.…

Machine Learning · Computer Science 2024-03-13 Robin Zbinden , Nina van Tiel , Marc Rußwurm , Devis Tuia

In ecology, the description of species composition and biodiversity calls for statistical methods that involve estimating features of interest in unobserved samples based on an observed one. In the last decade, the Bayesian nonparametrics…

Methodology · Statistics 2026-04-28 Alessandro Colombi , Raffaele Argiento , Federico Camerlenghi , Lucia Paci
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